
import pandas


df = pandas.read_csv('D:\CARLA\Portfolio\Estudos de Caso\Análise das Críticas Sobre Vinhos/winemag-data-130k-v2.csv')


df.head() #Dando uma olhada nos dados


df.dtypes #Verificando os tipos de dados.

Unnamed: 0                 int64
country                   object
description               object
designation               object
points                     int64
price                    float64
province                  object
region_1                  object
region_2                  object
taster_name               object
taster_twitter_handle     object
title                     object
variety                   object
winery                    object
dtype: object


df.count() #contando as ocorrências

Unnamed: 0               129971
country                  129908
description              129971
designation               92506
points                   129971
price                    120975
province                 129908
region_1                 108724
region_2                  50511
taster_name              103727
taster_twitter_handle     98758
title                    129971
variety                  129970
winery                   129971
dtype: int64


df.groupby('country').count()


df.groupby('taster_name').count()


df.taster_name

0              Kerin O’Keefe
1                 Roger Voss
2               Paul Gregutt
3         Alexander Peartree
4               Paul Gregutt
                 ...        
129966    Anna Lee C. Iijima
129967          Paul Gregutt
129968            Roger Voss
129969            Roger Voss
129970            Roger Voss
Name: taster_name, Length: 129971, dtype: object


df.loc[:,['country','points','price','province','taster_name','title','variety','winery']] 
#Vendo como funciona o comando loc (queria suprimir algumas colunas)


#Vamos ver quantas vezes os valores ocorreram?
df['taster_name'].value_counts()

Roger Voss            25514
Michael Schachner     15134
Kerin O’Keefe         10776
Virginie Boone         9537
Paul Gregutt           9532
Matt Kettmann          6332
Joe Czerwinski         5147
Sean P. Sullivan       4966
Anna Lee C. Iijima     4415
Jim Gordon             4177
Anne Krebiehl MW       3685
Lauren Buzzeo          1835
Susan Kostrzewa        1085
Mike DeSimone           514
Jeff Jenssen            491
Alexander Peartree      415
Carrie Dykes            139
Fiona Adams              27
Christina Pickard         6
Name: taster_name, dtype: int64


df_filtered = df[df['country'] == 'Brazil']


df_filtered.head()


df_filtered.count()

Unnamed: 0               52
country                  52
description              52
designation              51
points                   52
price                    47
province                 52
region_1                  0
region_2                  0
taster_name              52
taster_twitter_handle    52
title                    52
variety                  52
winery                   52
dtype: int64


df_filtered.to_csv('D:\CARLA\Portfolio\Estudos de Caso\Análise das Críticas Sobre Vinhos/Wine_Data_Brazil.csv', index = False)


df_brazil = pandas.read_csv('D:\CARLA\Portfolio\Estudos de Caso\Análise das Críticas Sobre Vinhos/Wine_Data_Brazil.csv')


df_brazil.head()


df_brazil_2 = df_brazil.loc[:,['country','points','price','province','taster_name','title','variety','winery']]


df_brazil_2


df_brazil_2.to_csv('D:\CARLA\Portfolio\Estudos de Caso\Análise das Críticas Sobre Vinhos/Wine_Data_Brazil_2.csv', index = False)


df_brazil_2 = pandas.read_csv('D:\CARLA\Portfolio\Estudos de Caso\Análise das Críticas Sobre Vinhos/Wine_Data_Brazil_2.csv')


df_brazil_2


df_brazil_2['price'].mean() #Média Price

23.76595744680851


df_brazil_2['price'].median() #Mediana Price

20.0


df_brazil_2['points'].mean() #Média Points

84.67307692307692


df_brazil_2['points'].median() #Mediana Points

85.0


import plotly.express as px


import plotly.figure_factory as ff


fig = px.box(df_brazil_2, y = "price")
fig.update_layout(title_text="Boxplot do Preço dos Vinhos no Brasil - Visualização 1", 
                  yaxis=dict(title_text="Preço-U$"))
fig.show("notebook")


fig = px.box(df_brazil_2, y = "price", points = "all")
fig.update_layout(title_text="Boxplot do Preço dos Vinhos no Brasil - Visualização 2", 
                  yaxis=dict(title_text="Preço-U$"))
fig.show("notebook")


df_brazil_2.groupby(['province']).agg({'points':'median', 'price':'median'}) #Conferindo a mediana por província do preço


fig = px.box(df_brazil_2, x = "province", y = "price", points = "all")

fig.update_layout(title_text="Boxplot do Preço dos Vinhos por Província - Brasil", 
                  yaxis=dict(title_text="Preço U$"),
                  xaxis=dict(title_text="Província"))
fig.show("notebook")


df_brazil_2.groupby(['winery']).agg({'points':'median', 'price':'median'})


fig = px.box(df_brazil_2, x = "winery", y = "price", points = "all")

fig.update_layout(title_text="Boxplot do Preço dos Vinhos por Vinícola - Brasil", 
                  yaxis=dict(title_text="Preço U$"),
                  xaxis=dict(title_text="Vinícola"))
fig.show("notebook")


df_brazil_2.groupby(['variety']).agg({'points':'median', 'price':'median'})


fig = px.box(df_brazil_2, x = "variety", y = "price", points = "all")

fig.update_layout(title_text="Boxplot do Preço dos Vinhos por Variedade - Brasil", 
                  yaxis=dict(title_text="Preço U$"),
                  xaxis=dict(title_text="Variedade"))
fig.show("notebook")

	Unnamed: 0	country	description	designation	points	price	province	region_1	region_2	taster_name	taster_twitter_handle	title	variety	winery
0	0	Italy	Aromas include tropical fruit, broom, brimston...	Vulkà Bianco	87	NaN	Sicily & Sardinia	Etna	NaN	Kerin O’Keefe	@kerinokeefe	Nicosia 2013 Vulkà Bianco (Etna)	White Blend	Nicosia
1	1	Portugal	This is ripe and fruity, a wine that is smooth...	Avidagos	87	15.0	Douro	NaN	NaN	Roger Voss	@vossroger	Quinta dos Avidagos 2011 Avidagos Red (Douro)	Portuguese Red	Quinta dos Avidagos
2	2	US	Tart and snappy, the flavors of lime flesh and...	NaN	87	14.0	Oregon	Willamette Valley	Willamette Valley	Paul Gregutt	@paulgwine	Rainstorm 2013 Pinot Gris (Willamette Valley)	Pinot Gris	Rainstorm
3	3	US	Pineapple rind, lemon pith and orange blossom ...	Reserve Late Harvest	87	13.0	Michigan	Lake Michigan Shore	NaN	Alexander Peartree	NaN	St. Julian 2013 Reserve Late Harvest Riesling ...	Riesling	St. Julian
4	4	US	Much like the regular bottling from 2012, this...	Vintner's Reserve Wild Child Block	87	65.0	Oregon	Willamette Valley	Willamette Valley	Paul Gregutt	@paulgwine	Sweet Cheeks 2012 Vintner's Reserve Wild Child...	Pinot Noir	Sweet Cheeks

	Unnamed: 0	description	designation	points	price	province	region_1	region_2	taster_name	taster_twitter_handle	title	variety	winery
country
Argentina	3800	3800	2902	3800	3756	3800	3747	0	3797	3797	3800	3800	3800
Armenia	2	2	2	2	2	2	0	0	2	2	2	2	2
Australia	2329	2329	1640	2329	2294	2329	2327	0	2037	2037	2329	2329	2329
Austria	3345	3345	2825	3345	2799	3345	0	0	3337	3337	3345	3345	3345
Bosnia and Herzegovina	2	2	1	2	2	2	0	0	2	1	2	2	2
Brazil	52	52	51	52	47	52	0	0	52	52	52	52	52
Bulgaria	141	141	93	141	141	141	0	0	141	122	141	141	141
Canada	257	257	179	257	254	257	257	0	256	241	257	257	257
Chile	4472	4472	3879	4472	4416	4472	0	0	4361	4361	4472	4471	4472
China	1	1	1	1	1	1	0	0	1	1	1	1	1
Croatia	73	73	48	73	71	73	0	0	73	34	73	73	73
Cyprus	11	11	9	11	11	11	0	0	11	11	11	11	11
Czech Republic	12	12	7	12	12	12	0	0	12	8	12	12	12
Egypt	1	1	1	1	0	1	0	0	1	1	1	1	1
England	74	74	74	74	69	74	0	0	74	74	74	74	74
France	22093	22093	14530	22093	17776	22093	22017	0	21828	21828	22093	22093	22093
Georgia	86	86	62	86	84	86	0	0	86	64	86	86	86
Germany	2165	2165	2006	2165	2120	2165	0	0	2134	375	2165	2165	2165
Greece	466	466	319	466	461	466	0	0	466	466	466	466	466
Hungary	146	146	124	146	145	146	0	0	145	113	146	146	146
India	9	9	4	9	9	9	0	0	9	9	9	9	9
Israel	505	505	435	505	489	505	0	0	500	500	505	505	505
Italy	19540	19540	13889	19540	16914	19540	19513	0	11042	11042	19540	19540	19540
Lebanon	35	35	30	35	35	35	0	0	35	25	35	35	35
Luxembourg	6	6	6	6	6	6	0	0	6	6	6	6	6
Macedonia	12	12	5	12	12	12	0	0	12	11	12	12	12
Mexico	70	70	53	70	70	70	0	0	65	65	70	70	70
Moldova	59	59	52	59	59	59	0	0	59	58	59	59	59
Morocco	28	28	16	28	28	28	0	0	28	26	28	28	28
New Zealand	1419	1419	684	1419	1378	1419	0	0	1311	1311	1419	1419	1419
Peru	16	16	16	16	16	16	0	0	16	16	16	16	16
Portugal	5691	5691	5105	5691	4875	5691	0	0	5686	5686	5691	5691	5691
Romania	120	120	114	120	120	120	0	0	120	79	120	120	120
Serbia	12	12	9	12	12	12	0	0	12	12	12	12	12
Slovakia	1	1	0	1	1	1	0	0	1	0	1	1	1
Slovenia	87	87	60	87	80	87	0	0	87	61	87	87	87
South Africa	1401	1401	822	1401	1293	1401	0	0	1328	1328	1401	1401	1401
Spain	6645	6645	5320	6645	6573	6645	6637	0	6581	6581	6645	6645	6645
Switzerland	7	7	3	7	7	7	0	0	7	7	7	7	7
Turkey	90	90	63	90	90	90	0	0	90	85	90	90	90
US	54504	54504	36908	54504	54265	54504	54226	50511	37730	34741	54504	54504	54504
Ukraine	14	14	12	14	14	14	0	0	14	12	14	14	14
Uruguay	109	109	95	109	109	109	0	0	109	109	109	109	109

	country	points	price	province	taster_name	title	variety	winery
0	Italy	87	NaN	Sicily & Sardinia	Kerin O’Keefe	Nicosia 2013 Vulkà Bianco (Etna)	White Blend	Nicosia
1	Portugal	87	15.0	Douro	Roger Voss	Quinta dos Avidagos 2011 Avidagos Red (Douro)	Portuguese Red	Quinta dos Avidagos
2	US	87	14.0	Oregon	Paul Gregutt	Rainstorm 2013 Pinot Gris (Willamette Valley)	Pinot Gris	Rainstorm
3	US	87	13.0	Michigan	Alexander Peartree	St. Julian 2013 Reserve Late Harvest Riesling ...	Riesling	St. Julian
4	US	87	65.0	Oregon	Paul Gregutt	Sweet Cheeks 2012 Vintner's Reserve Wild Child...	Pinot Noir	Sweet Cheeks
...	...	...	...	...	...	...	...	...
129966	Germany	90	28.0	Mosel	Anna Lee C. Iijima	Dr. H. Thanisch (Erben Müller-Burggraef) 2013 ...	Riesling	Dr. H. Thanisch (Erben Müller-Burggraef)
129967	US	90	75.0	Oregon	Paul Gregutt	Citation 2004 Pinot Noir (Oregon)	Pinot Noir	Citation
129968	France	90	30.0	Alsace	Roger Voss	Domaine Gresser 2013 Kritt Gewurztraminer (Als...	Gewürztraminer	Domaine Gresser
129969	France	90	32.0	Alsace	Roger Voss	Domaine Marcel Deiss 2012 Pinot Gris (Alsace)	Pinot Gris	Domaine Marcel Deiss
129970	France	90	21.0	Alsace	Roger Voss	Domaine Schoffit 2012 Lieu-dit Harth Cuvée Car...	Gewürztraminer	Domaine Schoffit

	Unnamed: 0	country	description	designation	points	price	province	region_1	region_2	taster_name	taster_twitter_handle	title	variety	winery
5852	5852	Brazil	Pear, apple and wet-stone aromas are tight, wh...	Brut	88	36.0	Pinto Bandeira	NaN	NaN	Michael Schachner	@wineschach	Cave Geisse 2014 Brut Sparkling (Pinto Bandeira)	Sparkling Blend	Cave Geisse
9151	9151	Brazil	This opens with dusty dried-apple aromas. High...	Brut	83	31.0	Santa Catarina	NaN	NaN	Michael Schachner	@wineschach	Villaggio Grando 2011 Brut Sparkling (Santa Ca...	Sparkling Blend	Villaggio Grando
10565	10565	Brazil	The name is appropriate: this is intense, just...	Intenso	84	NaN	Campanha	NaN	NaN	Michael Schachner	@wineschach	Salton 2013 Intenso Tannat (Campanha)	Tannat	Salton
10579	10579	Brazil	Roasted gritty aromas of asphalt and grilled b...	Intenso	84	NaN	Campanha	NaN	NaN	Michael Schachner	@wineschach	Salton 2013 Intenso Cabernet Franc (Campanha)	Cabernet Franc	Salton
12669	12669	Brazil	This Cabernet Sauvignon-Merlot blend almost ha...	Reserva	83	20.0	Serra Gaúcha	NaN	NaN	Michael Schachner	@wineschach	Château Lacave 2002 Reserva Cabernet Sauvignon...	Cabernet Sauvignon-Merlot	Château Lacave

	Unnamed: 0	country	description	designation	points	price	province	region_1	region_2	taster_name	taster_twitter_handle	title	variety	winery
0	5852	Brazil	Pear, apple and wet-stone aromas are tight, wh...	Brut	88	36.0	Pinto Bandeira	NaN	NaN	Michael Schachner	@wineschach	Cave Geisse 2014 Brut Sparkling (Pinto Bandeira)	Sparkling Blend	Cave Geisse
1	9151	Brazil	This opens with dusty dried-apple aromas. High...	Brut	83	31.0	Santa Catarina	NaN	NaN	Michael Schachner	@wineschach	Villaggio Grando 2011 Brut Sparkling (Santa Ca...	Sparkling Blend	Villaggio Grando
2	10565	Brazil	The name is appropriate: this is intense, just...	Intenso	84	NaN	Campanha	NaN	NaN	Michael Schachner	@wineschach	Salton 2013 Intenso Tannat (Campanha)	Tannat	Salton
3	10579	Brazil	Roasted gritty aromas of asphalt and grilled b...	Intenso	84	NaN	Campanha	NaN	NaN	Michael Schachner	@wineschach	Salton 2013 Intenso Cabernet Franc (Campanha)	Cabernet Franc	Salton
4	12669	Brazil	This Cabernet Sauvignon-Merlot blend almost ha...	Reserva	83	20.0	Serra Gaúcha	NaN	NaN	Michael Schachner	@wineschach	Château Lacave 2002 Reserva Cabernet Sauvignon...	Cabernet Sauvignon-Merlot	Château Lacave

Origem dos dados Analisados: Kaggle¶

Filtrar somente os dados relativos ao país BRAZIL¶

Salvar em um novo arquivo .csv os dados filtrados do Brazil¶

Quero tirar algumas colunas que não interessam - treinando comando .loc do pandas¶

Criar arquivo 2 com dados do Brazil e com as colunas que selecionei¶

Média e Mediana Gerais do Preço e Pontos (arquivo: Wine_Data_Brazil_2.csv)¶

BoxPlot do Preço dos Vinhos no Brasil¶

Boxplot do Preço dos Vinhos no Brazil por Província¶

Boxplot do Preço dos Vinhos no Brazil por Vinícola¶

Boxplot do Preço dos Vinhos no Brazil por Variedade¶

Fim Parte 1 - Agradeço seu feedback!! Por: Carla G. B. Teixeira¶

	points	price
province
Brazil	85.0	23.0
Campanha	84.0	26.0
Pinto Bandeira	87.5	30.5
Santa Catarina	84.5	33.0
Serra Gaúcha	85.0	15.0
Serra do Sudeste	82.0	15.0
Vale Trentino	86.0	20.0
Vale dos Vinhedos	85.0	30.0

	points	price
winery
Aurora Cellars	82.0	10.0
Casa Perini	85.0	15.0
Casa Valduga	85.5	25.0
Cave Geisse	87.5	30.5
Château Lacave	83.0	20.0
Lidio Carraro	85.0	15.0
Miolo	85.5	31.5
Pizzato	85.0	50.0
Salton	84.5	26.0
Villaggio Grando	84.5	33.0
Vinícola Aurora	82.0	15.0

	points	price
variety
Bordeaux-style Red Blend	84.0	22.5
Cabernet Franc	84.0	NaN
Cabernet Sauvignon	83.0	27.5
Cabernet Sauvignon-Merlot	83.0	20.0
Champagne Blend	86.0	23.0
Chardonnay	82.0	20.0
Merlot	85.0	15.0
Merlot-Cabernet Sauvignon	85.5	39.0
Moscatel	87.0	22.5
Moscato	84.5	15.0
Pinot Noir	86.0	25.0
Red Blend	86.0	26.0
Sparkling Blend	85.5	28.5
Tannat	84.0	15.0